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The features of turbulence modulation produced by a heavy loaded suspension of small solid particles or liquid droplets are discussed by using a physically-based regularisation of particle-fluid interactions. The approach allows a robust…

Fluid Dynamics · Physics 2017-04-05 P. Gualtieri , F. Battista , C. M. Casciola

The reliability of any day-to-day material is critically dictated by its properties. One factor which governs the behaviour of a material, under a given condition, is the microstructure. Despite the absence of any phase transformation, a…

Materials Science · Physics 2019-06-26 P G Kubendran Amos

In this work we present a theoretical study on the propagation of light in heterogeneous systems with fluctuating optical properties. To understand the consequences of the fluctuations we perform numerical calculations with uniform and non…

Optics · Physics 2015-07-07 Emiliano Terán-Bobadilla , Eugenio Méndez

In this article, we report a fully ab initio variational Monte Carlo study of the linear, and periodic chain of Hydrogen atoms, a prototype system providing the simplest example of strong electronic correlation in low dimensions. In…

Strongly Correlated Electrons · Physics 2015-05-30 Lorenzo Stella , Claudio Attaccalite , Sandro Sorella , Angel Rubio

The projective quantum Monte Carlo (PQMC) algorithms are among the most powerful computational techniques to simulate the ground state properties of quantum many-body systems. However, they are efficient only if a sufficiently accurate…

Computational Physics · Physics 2019-10-04 S. Pilati , E. M. Inack , P. Pieri

A discrete model for computer simulations of the clustering dynamics of Social Amoebae is presented. This model incorporates the wavelike propagation of extracellular signaling cAMP, the sporadic firing of cells at early stage of…

Cell Behavior · Quantitative Biology 2013-05-14 Yipeng Yang , Y. Charles Li

By the Wolff's cluster Monte Carlo simulations and numerical minimization within a mean field approach, we study the low temperature phase diagram of water, adopting a cell model that reproduces the known properties of water in its fluid…

Soft Condensed Matter · Physics 2009-11-13 Marco G. Mazza , Kevin Stokely , Elena Strekalova , H. Eugene Stanley , Giancarlo Franzese

Monte Carlo simulations of coarse-grained polymers provide a useful tool to deepen the understanding of conformational and statistical properties of polymers both in physical as well as in biological systems. In this study we sample compact…

Soft Condensed Matter · Physics 2009-05-07 Manfred Bohn , Dieter W. Heermann

A diffusion Monte Carlo algorithm is introduced that can determine the correct nodal structure of the wave function of a few-fermion system and its ground-state energy without an uncontrolled bias. This is achieved by confining signed…

Computational Physics · Physics 2020-02-05 Alexander A. Kunitsa , So Hirata

Complex soft matter systems can be efficiently studied with the help of adaptive resolution simulation methods, concurrently employing two levels of resolution in different regions of the simulation domain. The non-matching properties of…

We develop exact Markov chain Monte Carlo methods for discretely-sampled, directly and indirectly observed diffusions. The qualification "exact" refers to the fact that the invariant and limiting distribution of the Markov chains is the…

Monte Carlo methods play an important role in scientific computation, especially when problems have a vast phase space. In this lecture an introduction to the Monte Carlo method is given. Concepts such as Markov chains, detailed balance,…

Statistical Mechanics · Physics 2011-05-05 Helmut G. Katzgraber

Among many types of quantum entanglement properties, the entanglement spectrum provides more abundant information than other observables. Exact diagonalization and density matrix renormalization group method could handle the system in…

Strongly Correlated Electrons · Physics 2025-03-05 Weilun Jiang , Xiaofan Luo , Bin-Bin Mao , Zheng Yan

In this work we present the general phase behavior of short tubelike flexible polymers. The geometric thickness constraint is implemented through the concept of the global radius of curvature. We use sophisticated Monte Carlo sampling…

Soft Condensed Matter · Physics 2009-07-20 Thomas Vogel , Thomas Neuhaus , Michael Bachmann , Wolfhard Janke

Quantum nanosystems involve the coupled dynamics of fermions or bosons across multiple scales in space and time. Examples include quantum dots, superconducting or magnetic nanoparticles, molecular wires, and graphene nanoribbons. The number…

Mesoscale and Nanoscale Physics · Physics 2011-11-01 D. Balamurugan , Peter. J. Ortoleva

Due to the complex characteristics of bottle-brush polymers, it became a challenge to develop an efficient algorithm for studying such macromolecules under various solvent conditions or some constraints in the space by using computer…

Soft Condensed Matter · Physics 2011-07-08 Hsiao-Ping Hsu

Quantum tunneling is a valuable resource exploited by quantum annealers to solve complex optimization problems. Tunneling events also occur during projective quantum Monte Carlo (PQMC) simulations, and in a class of problems characterized…

Quantum Physics · Physics 2019-12-16 T. Parolini , E. M. Inack , G. Giudici , S. Pilati

In an attempt to describe the change of topological structure of pure SU(2) gauge theory near deconfinement a renormalization group inspired method is tested. Instead of cooling, blocking and subsequent inverse blocking is applied to Monte…

High Energy Physics - Lattice · Physics 2009-10-30 M. Feurstein , E. -M. Ilgenfritz , H. Markum , M. Müller-Preussker , S. Thurner

Quantitative long-time entropic convergence and short-time regularization are established for an idealized Hamiltonian Monte Carlo chain which alternatively follows an Hamiltonian dynamics for a fixed time and then partially or totally…

Probability · Mathematics 2023-06-06 Pierre Monmarché

Many problems require to approximate an expected value by some kind of Monte Carlo (MC) sampling, e.g. molecular dynamics (MD) or simulation of stochastic reaction models (also termed kinetic Monte Carlo (kMC)). Often, we are furthermore…

Numerical Analysis · Mathematics 2019-02-18 Sandra Döpking , Sebastian Matera